Most asked
What is an AI agent, and how is it different from a chatbot?
Short answer
A chatbot answers. An agent acts. An agent combines reasoning, memory, and access to tools so it can carry out multi-step work: retrieve information, interpret it, update another system, and follow up. That shift from producing an answer to taking an action is what changes both the value and the risk.
The clean distinction is answer versus action.
A chatbot can tell you which invoices are overdue. An agent can identify the overdue invoices, pull the account history, draft the follow-up messages, place them in an approval queue, and update the record once someone approves. Same underlying technology, fundamentally different capability.
Three components make that possible. A model that does the reasoning. Tools it can actually reach, such as an application programming interface or a database. And instructions that set both the objective and the boundaries. That third component is the one executives should ask about, because it is where the guardrails live and it is the easiest to leave vague.
The line is blurring, because the major platforms increasingly do both. What matters for a decision-maker is not the label but the consequence. As soon as a system can write to a database, send something to a customer, change a record, or start a workflow, its mistakes produce operational effects rather than a bad paragraph you can delete. Permissions, logging, approval points, and the ability to stop it become substantially more important than they ever were for a question-and-answer tool.
Worth setting expectations honestly. A lot of what is being built right now is eager rather than experienced. These systems ask too many clarifying questions, misread situations, and occasionally return results that create work rather than remove it. That is a reason to scope carefully, not a reason to wait.